Data on land use and land cover changes in Adama Wereda, Ethiopia, on ETM+, TM and OLI- TIRS landsat sensor using PCC and CDM techniques
Land use and land cover changes are often referred for the anthropogenic modification of Earth's surface. The extents of land use and land cover (LULC) changes in Adama Wereda at three different periods (2002, 2010, and 2017) were generated using data from various Landsat sensors namely ETM+, T...
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019-06-01
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| Series: | Data in Brief |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340919302318 |
| _version_ | 1811286554281246720 |
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| author | A.S. Mohammed Abdul Athick K. Shankar |
| author_facet | A.S. Mohammed Abdul Athick K. Shankar |
| author_sort | A.S. Mohammed Abdul Athick |
| collection | DOAJ |
| description | Land use and land cover changes are often referred for the anthropogenic modification of Earth's surface. The extents of land use and land cover (LULC) changes in Adama Wereda at three different periods (2002, 2010, and 2017) were generated using data from various Landsat sensors namely ETM+, TM and OLI TIRS. This work focused on a change detection analysis using post classification comparison (PCC) and change detection matrix (CDM). These images were geometrically corrected and image processing operations for instance: radiometric correction, using spectral radiance model was carried out, followed by land cover categorisation into water bodies, built up, bare land, sparse vegetation and dense vegetation employing Knowledge, pixel and indices based classification in ERDAS imagine software. The generated data of both change detection techniques from 2002 to 2017 revealed interesting aspect that build up, dense vegetation and sparse vegetation increased in area of approximately 160%, 30% and 78% respectively at the expense of barren land which decreased at 8.5%, but there is not much change in the water bodies. It was also noticed that both the algorithms gives similar values but with negligible deviation. Keywords: Land use and land cover (LULC), Change detection, Remote sensing, Landsat sensors, Post classification comparison, Change detection matrix |
| first_indexed | 2024-04-13T03:02:58Z |
| format | Article |
| id | doaj.art-427009dbf5b048bbb7c4625ff0258ff6 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-04-13T03:02:58Z |
| publishDate | 2019-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-427009dbf5b048bbb7c4625ff0258ff62022-12-22T03:05:22ZengElsevierData in Brief2352-34092019-06-0124Data on land use and land cover changes in Adama Wereda, Ethiopia, on ETM+, TM and OLI- TIRS landsat sensor using PCC and CDM techniquesA.S. Mohammed Abdul Athick0K. Shankar1Department of Geomatics Engineering, School of Civil Engineering and Architecture, Adama Science & Technology University, EthiopiaDepartment of Applied Geology, School of Applied Natural Science, Adama Science & Technology University, Ethiopia; Corresponding author.Land use and land cover changes are often referred for the anthropogenic modification of Earth's surface. The extents of land use and land cover (LULC) changes in Adama Wereda at three different periods (2002, 2010, and 2017) were generated using data from various Landsat sensors namely ETM+, TM and OLI TIRS. This work focused on a change detection analysis using post classification comparison (PCC) and change detection matrix (CDM). These images were geometrically corrected and image processing operations for instance: radiometric correction, using spectral radiance model was carried out, followed by land cover categorisation into water bodies, built up, bare land, sparse vegetation and dense vegetation employing Knowledge, pixel and indices based classification in ERDAS imagine software. The generated data of both change detection techniques from 2002 to 2017 revealed interesting aspect that build up, dense vegetation and sparse vegetation increased in area of approximately 160%, 30% and 78% respectively at the expense of barren land which decreased at 8.5%, but there is not much change in the water bodies. It was also noticed that both the algorithms gives similar values but with negligible deviation. Keywords: Land use and land cover (LULC), Change detection, Remote sensing, Landsat sensors, Post classification comparison, Change detection matrixhttp://www.sciencedirect.com/science/article/pii/S2352340919302318 |
| spellingShingle | A.S. Mohammed Abdul Athick K. Shankar Data on land use and land cover changes in Adama Wereda, Ethiopia, on ETM+, TM and OLI- TIRS landsat sensor using PCC and CDM techniques Data in Brief |
| title | Data on land use and land cover changes in Adama Wereda, Ethiopia, on ETM+, TM and OLI- TIRS landsat sensor using PCC and CDM techniques |
| title_full | Data on land use and land cover changes in Adama Wereda, Ethiopia, on ETM+, TM and OLI- TIRS landsat sensor using PCC and CDM techniques |
| title_fullStr | Data on land use and land cover changes in Adama Wereda, Ethiopia, on ETM+, TM and OLI- TIRS landsat sensor using PCC and CDM techniques |
| title_full_unstemmed | Data on land use and land cover changes in Adama Wereda, Ethiopia, on ETM+, TM and OLI- TIRS landsat sensor using PCC and CDM techniques |
| title_short | Data on land use and land cover changes in Adama Wereda, Ethiopia, on ETM+, TM and OLI- TIRS landsat sensor using PCC and CDM techniques |
| title_sort | data on land use and land cover changes in adama wereda ethiopia on etm tm and oli tirs landsat sensor using pcc and cdm techniques |
| url | http://www.sciencedirect.com/science/article/pii/S2352340919302318 |
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